Abstract! Approximately half of the 1.6 million people diagnosed with cancer in 2013 in the United States will receive radiation therapy in the management of their disease. Because each course of radiation therapy is tailored to the disease and anatomy of the patient, delivery of the intended dose is dependent upon, in part, the ability of the treatment machine to reproduce the planned treatment parameters. Despite this, the current quality assurance paradigm in radiation oncology does not provide independent verification that the plan has been correctly delivery each time the patient has been treated. Indeed, current practice is largely dependent upon internal safeguards deployed by the linear accelerator manufacturer to recognize meaningful system deviations and terminate delivery accordingly. The motivation for this application is an urgent need for commercial tools that improve confidence in daily treatment of every radiation therapy patient. The overarching hypothesis of this proposal is that treatment delivery log files produced by the treatment delivery system can be combined with an independent dose calculation algorithm, and, eventually, patient positioning information to provide daily verificatin of the delivered dose and significantly improve estimates of the dose received by the patient. The system will provide significant enhancements in patient safety in radiation therapy, and will have important applications in adaptive therapy, performance monitoring, and statistical process control. The Phase I goals are to (i) to demonstrate the feasibility of the system to provide accurate estimates of the daily delivered dose and (ii) to build a framework for incorporating future extensions, such as incorporating daily localization images, in the daily dose reconstruction process. The proposed system will be developed using sample data collected from our academic partner. Treatment delivery data will be extracted from linear accelerator log files and passed to an independent dose calculation algorithm. The resulting 3D dose distribution will be calculated and compared with the planned distribution. The user will then be automatically notified if pre-determined dosimetric thresholds set by the user are exceeded. The clinical functionality of the system will be assessed through deployment in the clinical setting and the accuracy of the system will be assessed by comparing its dose calculations with simultaneous physical measurements of the delivered dose distribution. !